A Review of Demand Models for Water Systems in Buildings including a Bayesian Approach

Abstract

Instantaneous flow rate estimation is essential for sizing pipes and other components of water systems in buildings. Although various demand models have been developed in line with design and technology trends, most water supply system designs are routinely and substantially over-sized to keep failure risks to a minimum. Three major types of demand models from the literature are reviewed in this paper: (1) deterministic approach; (2) probabilistic approach; and (3) demand time-series approach. As findings show some widely used model estimates are much larger than the field measurements, this paper proposes a Bayesian approach to bridge the gap between model-based and field-measured values for the probable maximum simultaneous water demand. The proposed approach is flexible to adopt estimates as its prior values from a wide range of existing water demand models for determining the Bayesian coefficients for reference models, codes, and design standards with relevant measurement data. The approach provides a useful method not only for evaluating the corresponding demand values from various design references, but also for responding to the call for sustainable building design.